Single-cell profiling identifies a CD8bright CD244bright Natural Killer cell subset that reflects disease activity in HLA-A29-positive birdshot chorioretinopathy

Birdshot chorioretinopathy is an inflammatory eye condition strongly associated with MHC-I allele HLA-A29. The striking association with MHC-I suggests involvement of T cells, whereas natural killer (NK) cell involvement remains largely unstudied. Here we show that HLA-A29-positive birdshot chorioretinopathy patients have a skewed NK cell pool containing expanded CD16 positive NK cells which produce more proinflammatory cytokines. These NK cells contain populations that express CD8A which is involved in MHC-I recognition on target cells, display gene signatures indicative of high cytotoxic activity (GZMB, PRF1 and ISG15), and signaling through NK cell receptor CD244 (SH2D1B). Long-term monitoring of a cohort of birdshot chorioretinopathy patients with active disease identifies a population of CD8bright CD244bright NK cells, which rapidly declines to normal levels upon clinical remission following successful treatment. Collectively, these studies implicate CD8bright CD244bright NK cells in birdshot chorioretinopathy.


INTRODUCTION
Non-infectious uveitis (NIU) is a clinically and prognostically heterogeneous group of ocular inflammatory diseases and a major cause of severe visual handicap 1 . Birdshot chorioretinopathy (Birdshot Uveitis or BCR-UV) is a relatively rare form of NIU that has clinically distinct features in the form of retinal and choroidal inflammatory lesions visible on examination. BCR-UV can lead to progressive deterioration of visual function 2,3,4 due to persistent inflammation in the retina and choroid 5 . Consequently, patients often require systemic immunomodulatory therapy to control ocular inflammation 3,6 . The disease mechanisms driving BCR-UV remain to be elucidated, but scientific advances have shed light on the immunopathology of this clinically well-defined ophthalmological condition 7 .
One of the most striking molecular features of BCR-UV is that it's strongly associated with the presence of HLA-A29 allele such that all patients carry the HLA-A29 allele (most often the common HLA-A*29:02) 7,8 . Genome-wide genetic studies have revealed that the susceptibility to BCR-UV also maps to other factors of the MHC-I pathway 9,10,11 . This incriminates CD8+ T cells and Natural Killer (NK) cells in the pathogenesis of BCR-UV 7 . Indeed, CD8+ T cells have been shown to infiltrate eye tissues of patients and secrete cytokines considered central to its immunopathology 12,13,14,15 .
The role of NK cells in BCR-UV has remained significantly underexplored. Classically, blood NK cells are subdivided into two well-established overarching populations; the CD56 dim CD16+ NK cells (~90% of circulating NK cells) also known as NK1 cells which are considered to be cytotoxic and produce greater amounts of pro-inflammatory cytokines and the CD56 bright (~10% of circulating NK cells) -or NK2 cells -that are considered to be more immunoregulatory 16 . Of interest, CD56 bright NK cells have been shown to be lower in patients with NIU, including BCR-UV patients with active uveitis 17 and successful immunosuppressive treatment of NIU is accompanied by the recovery of CD56 bright NK cell levels 18 . However, beyond this phenotypic bifurcation, NK cell population is substantially more diverse and thus far single-cell RNA sequencing (scRNAseq) has uncovered at least 10 transcriptionally distinct clusters in peripheral blood 19,20,21 . This includes 'inflammatory' CD56 dim CD16+ NK subsets that was defined by high levels of cytokine and interferon response genes 20,21 and "adaptive-like" NK populations that expand during infection 22 .
Transcriptomically distinct NK cell subsets are considered to exhibit differential effector functions mediated by an ensemble of surface immunoregulatory molecules 23 , in particular Killer cell immunoglobulin-like receptors (KIR), IgG Fc receptors (e.g., CD16), and integrins (e.g., CD47) 24,25,26 . Perturbations in the composition of the NK cells have been reported in other MHC-I associated conditions, such as HLA-B27-positive ankylosing spondylitis 27 and were shown to be predictive for clinical outcome in autoimmune diseases, such as Multiple Sclerosis 28 . Collectively, these observations suggest that deep phenotyping of the blood NK cell compartment could provide better understanding of disease biology and may hold clinically relevant information to the clinical course of BCR-UV.
Here, we have taken a multi-omics approach to phenotype the NK cell compartment at single-cell resolution of patients with BCR-UV and report on the expansion of a CD56 dim CD16+ subset of NK cells which are CD8 bright and CD244 bright , and whose reduction is correlated with clinical improvement after systemic immunosuppressive therapy.

Increased frequency of CD16+ NK cells in Birdshot uveitis patients
To investigate the relationship between NK cell-mediated inflammation and BCR-UV, we first sought evidence that circulating NK cells were specifically perturbed in BCR-UV.
To this end, we quantified the major lineages of immune cells (10-marker panel, 6 lineages) ( Supplementary Fig. 1A) in peripheral blood using flow cytometry in a cohort of 18 BCR-UV patients, 80 healthy controls, and 121 non-infectious uveitis (NIU) patients other than BCR-UV (Fig. 1A). Global comparison of major lineages in all NIU patients versus healthy controls revealed a significant increase in frequency of blood NK cells (Fig. 1B), but not T cells, B cells, monocytes, or dendritic cells (Supplementary Fig. 1B-D). Flow cytometry analysis revealed that blood NK cell frequency appeared to be increased in several uveitis subtypes, but this increase was most significant for BCR-UV (P < 0.0001) (Fig. 1C). This became more evident after quantification of the two major A. Schematic representation of flow cytometry of major immune cell lineages in fresh peripheral blood of 139 uveitis patients (UV) and 80 age-, sex-matched healthy controls (HC). B. Flow-cytometry quantification of the percentage of NK cells in the peripheral blood of uveitis patients (Uveitis) compared to healthy controls (Healthy). C. Flow-cytometry analysis of NK cells (CD3 -CD19 -CD56 + ) in the fresh blood of different uveitis subgroups indicate the significant expansion of NK cells were restricted to birdshot, definite sarcoidosis, serpiginous and undifferentiated sub-groups of uveitis cohort. P values are from unpaired t test. **** P < 0.0001, *** P = 0.0002, ** P = 0.004, * P = 0.01. D. The flow-cytometry gating strategy for NK1 and NK2 subsets of NK cells using CD56 and CD16 in peripheral blood. E. NK cell and NK1 and NK2 subset quantification in peripheral blood of birdshot uveitis (BCR-UV) and age-matched healthy controls (HC). HC n = 15; BCR-UV n = 18. F. Histogram of the fluorescence intensity of intracellular effector molecules produced by NK cells and determined by flow cytometry analysis upon stimulation with Lymphocyte Activation Cocktail (BD All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Biosciences. Analysis was conducted using PBMCs from BCR-UV (red) and NK cells from healthy controls (HC, blue). HC n = 8; BCR-UV n = 8.
NK populations (i.e., NK1, and NK2) that can be distinguished by their expression of surface CD56 and CD16 (Fig. 1D). We detected a significant increase of CD56 dim CD16+ [NK1] cells and a concomitant decrease of the CD56 bright CD16 -[NK2] cells only in BCR-UV patients or when considering all NIU patients collectively, but not individually in any of the other types of NIU ( Supplementary Fig. 1E-F). This skew in NK1/NK2 balance also remained evident after strict comparison to 15 age-matched healthy controls (mean age±SD = 62.2±8.8) (Fig. 1E).
Importantly, NK cells of BCR-UV patients showed enhanced responsiveness to restimulation by production of significantly higher tumor necrosis factor-ɑ (TNF-ɑ, P = 0.007) and interferon-γ (IFN-γ, P = 0.002) (Fig. 1F), indicating that the altered NK1/NK2 balance results in a more pro-inflammatory NK repertoire. Collectively, these data show an imbalance in NK1/NK2 cells in peripheral blood of patients with BCR-UV and a skew towards a more proinflammatory phenotype.

PBMC scRNA-seq identifies altered NK repertoire in Birdshot Chorioretinopathy
To allow characterization of the changes in peripheral blood NK cells in BCR-UV in an unbiased manner, we used single-cell RNA-sequencing (scRNAseq) of peripheral blood mononuclear cells (~300K cells) of 24 BCR-UV patients and healthy controls ( Fig. 2A and Supplementary Fig. 2A). Unsupervised clustering followed by uniform manifold approximation and projection (UMAP) and automated cell type annotation, identified an NK cell population (9,619 cells of cluster C4, Fig. 2B and Supplementary Fig. 2B) with an altered NK cluster structure in two-dimensional UMAP space in BCR-UV patients compared to healthy controls ( Supplementary Fig. 2C). NK-specific GZMB (granzyme B), KLRD1, GNLY, PRF1 (perforin), NKG7 and SH2D1B (CD244 signaling) were among the most differentially upregulated genes in BCR-UV ( Supplementary Fig. 2D). We extracted the NK cells from the PBMC scRNAseq data for further analysis.
Unsupervised clustering of the NK cell population revealed a high level of transcriptomic heterogeneity and the existence of 12 distinct clusters ranging from 57 cells (cluster 11) to 2,093 cells (cluster 0) in each cluster ( Fig. 2C and Supplementary Fig. 3A). Gene expression levels of characteristic NK lineage surface markers revealed that these All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this this version posted September 15, 2022. ; https://doi.org/10.1101/2022.09.11.22279821 doi: medRxiv preprint preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.  All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
We further observed that cluster 10 showed high CD244 (Fig. 2D, F) and clusters 2 and 10 displayed enrichment of CD244 binding Src homology 2 (SH2) domain-encoding genes SH2D2A and SH2D1B, which control signal transduction through the surface receptor CD244 29 (Fig. 2F). This implicates active CD244 signaling in these NK clusters.
Other highly expressed activation-associated genes in these sub-clusters include TNFRSF18 (also known as GITR) and ISG15 (Interferon-Stimulated Protein, 15 kDa) analyses are CD56 dim and CD16+ populations. Differential cluster abundance analysis revealed that clusters 4 and 5 were significantly reduced in the BCR-UV, while cluster 0 was significantly increased (Fig. 3B, C). The NK2 cluster 4 was further defined by high expression of CD336 and CD94 whereas the expanded NK1 cluster 0 was defined by All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.  All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
We determined by in vitro culture that CD244 expression but not CD8 was upregulated in NK cells by restimulation with IL-15 and IL-18, indicating that CD8a+ CD244+ cells may represent activated CD8+ NK cells (Fig. 3F). To validate these findings, we year of treatment and normalized to the frequency observed in healthy controls (P < 0.05) (Fig. 4C, D). In conclusion, these results show that CD8a bright /CD244 bright NK1 cells are expanded during active uveitis in BCR-UV patients but decrease upon successful systemic immunomodulatory treatment and clinical remission, compatible All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.  All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this this version posted September 15, 2022. ; https://doi.org/10.1101/2022.09.11.22279821 doi: medRxiv preprint with the interpretation that CD8a bright /CD244 bright NK1 cells are a pro-inflammatory NK subset that are likely to be involved in the underlying disease mechanism.

DISCUSSION
In this study, we conducted deep molecular phenotyping of peripheral blood NK cells and identified altered changes in NK1/NK2 subsets in peripheral blood of BCR-UV patients. We found expansion of a CD8a bright CD244 bright NK1 subset in BCR-UV patients that decreased upon successful treatment with systemic immunomodulatory therapy.
Our findings also corroborate previous reports on the decreased CD56 bright NK cells (NK2) in BCR-UV 17 and the normalization of CD56 bright NK cell abundance upon immunosuppressive treatment of non-infectious uveitis 18 . In other MHC-I associated conditions, such as HLA-B51-associated Behcet's disease (BD) and HLA-B27associated ankylosing spondylitis (AS), NK1/NK2 changes have been reported. In BD, total NK cells are increased in frequency in blood 31, 32 and produce increased IFNgamma and TNF-alpha 33,34 , which we also demonstrate in BCR-UV. In AS, the number of CD56 dim CD16+ subset of NK cells (NK1) in the peripheral blood is increased, 35,36,37 which is in line with our finding of elevated CD16+ CD56 dim NK cells in BCR-UV. Here, we add to these previous observations that the decline in CD56 bright regulatory NK cells in BCR-UV is accompanied by a concomitant expansion of CD56 dim CD16+ NK cells, that also express the alpha-chain of the CD8 co-receptor for HLA class I 38, 39 , advancing the understanding of NK cell dynamics in ocular inflammatory disease. The subset of CD8+ NK cells (also known as "NK8 + " cells 28 ) make up approximately half of the blood NK cells 40 and are found in both the CD56 dim CD16+ and CD56 bright CD16+ NK subsets ( Supplementary Fig. 6A). Note that in contrast to CD8+ T cells, which express the alpha and beta chain of CD8, NK8 + cells only express the alpha chain of CD8 and mouse NK cells do not express CD8 at all 38,39 .
NK8 + cells are considered to be functionally distinct and produce more IFN-gamma and TNF-alpha compared to CD8 -NK cells 41 . Accordingly, our data show that the NK8 +enriched population in patients secretes more IFN-gamma and TNF-alpha compared to healthy controls. In addition, the activation marker CD69 was increased in patients ( Supplementary Fig. 6B) and was induced upon treatment with IL-15 or IL-18 (Fig. 3F).
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The copyright holder for this this version posted September 15, 2022. ; https://doi.org/10.1101/2022.09.11.22279821 doi: medRxiv preprint This is significant because cross-linking of CD8 on NK cells induces increased expression of the activation marker CD69 at the cell surface 42 . Of interest, elevated frequency of peripheral blood NK8 + cells with homing marker CXCR3 is associated with an increased risk for Type 1 diabetes, a T-cell mediated autoimmune condition 43 . The most expanded NK8 + subpopulation identified by scRNAseq (cluster 10) in BCR patients was also characterized by high CXCR3 expression (Supplementary Fig. 3C).
Whether this NK8 + subset (i.e., cluster 10) may directly contribute to eye inflammation in BCR-UV, remains to be determined. Alternatively, the NK8 + skewing may be a reflection of diminished regulatory capacity in the NK cell compartment. NK cells are required to suppress CD8+ T cell autoimmunity 44 which is attributed to the negative immunoregulation of activated T cells by CD56 bright NK cells 45 . As shown in this study, We showed that the CD244 bright NK8 + cells correlate with disease activity during longitudinal monitoring of patients treated with systemic immunomodulatory therapy. The NK8 + cell frequency has previously been shown to correlate with clinical parameters in All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
It would be interesting to use flow cytometry analysis of this cell subset to see if its abundance can be used to predict treatment outcome or clinical course in advance (measured at diagnosis).
In conclusion, using complementary immunophenotyping platforms, we identified an expanded CD8a bright CD244 bright population of circulating NK cells in BCR-UV whose abundance reflects inflammatory disease activity. Better understanding of the molecular underpinnings of BCR-UV and its relation to clinical outcome may pave the way towards implementation of more effective personalized therapeutic approaches in ocular inflammatory diseases. All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

Blood sample processing
Blood samples from patients and healthy controls are collected through venipuncture and all the samples were processed within 4 h of blood collection. Fresh whole-blood samples were directly used for flow cytometry analysis. PBMCs were purified by standardized density gradient isolation (Ficoll-Paque) and stored in liquid nitrogen until further use.

Flow cytometry
Three mL of whole blood was incubated with 30 mL 1x RBC lysis buffer (BioLegend #420391) at room temperature for 15 minutes, centrifuged at 400 x g for 5 minutes and resuspended in 3 ml ACK lysis buffer (Lonza #BP10-548E) for 4 minutes at room temperature. Cell suspension was washed in a 30 ml FACS buffer (FB: 1x PBS w/o calcium and magnesium chloride + 2 % FBS + 2 mM EDTA + 0.01 % NaN3). In total, 1- streptavidin were used for secondary staining. The Pe/Cy7 Lin cocktail in monocyte/DC panel includes anti-human CD3, CD19, CD20 and CD56 Antibodies. Live/dead staining was carried out using Fixable Viability Dye eFluor® 455UV concomitantly with surface All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
Data were analyzed using FlowJo v10. For ex vivo restimulation, NK cells from a healthy donor were cultured with recombinant human IL-15 and IL-18 using five serial dilutions as indicated of ED50 concentrations. Cell-surface expression of CD69, CD244 and CD8 was measured using a BD LSRFortessa and analyzed by FlowJo V.10.

FlowSOM analysis
Live NK cells (Aqua L/D-CD3-CD20-CD56+) were gated from 18 BCR-UV patients sampled at baseline (i.e., at disease onset or relapse) and 10 healthy controls. NK cell fraction (range 5,011 to 42,358 NK cells) was down-sampled to 5,000 NK cells per donor using FlowJo DownsampleV3 plugin, concatenated and subjected to t-distributed stochastic neighbor embedding (t-SNE, iteration 1000, perplexity 30). The FlowSOM plugin in FlowJo was used to cluster cells into 12 meta-clusters (following 12 clusters identified in scRNAseq). All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

Preprocessing of scRNAseq data
The raw fastq data were processed using cellranger v6.0.0 49 with genome assembly GRCh38 (hg38), 3' and 5' assay chemistry SC3Pv3, and an expected cell count of 10,000 per sample (Supplementary Table 5). Further analysis of the single cell data was done using the Seurat v4.0.5 50 package in the R v4.1.0 environment 51 . Cells with fewer than 300 genes and number of transcript counts less than 1,000 and more than 12,000, more than 8% mitochondrial and 40% ribosomal fraction were excluded from the dataset. Doublets were detected and removed using the doubletFinder v3.0 package 52 in R, set with an expected doublet level of 7%. Data were normalized using the "LogNormalize" method with the scaling factor set at 10,000. The variables, sample batch, percent mitochondria, percent ribosomes, transcript counts and gene counts, were regressed out using the ScaleData function.

Dimension reduction, clustering and visualization
Cells were clustered using Principal Component Analysis (PCA) using the RunPCA function. The first 20 PCs identified (by Elbow method) were used in the 'FindNeighbors' (based on k-nearest neighbor (KNN) graphs) and 'FindCluster' (Louvain algorithm) functions in Seurat. RunTSNE and RunUMAP functions were used with "pca" as the reduction method, to visualize the data. The FindAllMarkers function was used to All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this this version posted September 15, 2022. ; https://doi.org/10.1101/2022.09.11.22279821 doi: medRxiv preprint identify cluster specific markers. Cell type annotation was generated manually combining automatic annotation results from ScType 53 , with "Immune System" set as the tissue type, and SCSA 54 , with the whole database as reference. Outcomes from ScType and SCSA were used to curate cluster annotation and identify NK cells by plotting expression of lineage-specific genes. Differences in proportions of scRNAseq data between the groups were assessed using the "scProportionTest" package 55 , with number of permutations set at 10,000.

Data availability
All raw data and workflow are available as an open-source resource, with documentation. All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
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Figure S1
A. List of markers for interrogating major lineages of immune cells (10 markers, 6 major immune subsets) in peripheral blood of patients and healthy controls using flow cytometry. Representative plot and frequency of (B) T cells, (C) B cells, (D) monocyte and (DCs) and (E) NK cells and in the peripheral blood of uveitis patients (blue) and healthy controls are shown. There was no change in the frequency of T cells, B cells, DCs and monocytes, except the differences found in the NK cell subsets between the two groups. CD56highCD16-NK cells were significantly decreased while concomitantly CD56loCD16+ NK cells were significantly increased in uveitis cohort compared to the healthy controls. F. Flow-cytometry analysis of NK1 (CD56dim CD16+) and NK2 (CD56bright) NK cells (CD3 -CD19 -CD56 + ) in the fresh blood of different uveitis subgroups.
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Figure S3
A. Tabular representation of total 12 NK-subclusters and associated cell count in 12 healthy controls (HC) and in 12 birdshot uveitis patients (BCR-UV). B. Violin plots representing the list of genes that are uniquely expressed in each of the 12 clusters of NK cell-subclusters. C. Heatmap representing the expression of top 10 highly expressed markers of each NK cluster. D. Heatmap representing the expression of top 10 differentially expressed markers of each NK cluster.
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Figure S4
A. List of markers used to interrogate NK lineage cells in peripheral blood of BCR-UV patients and healthy controls using flow cytometry. B. t-SNE plot represents the FlowJo-based FlowSOM analysis to identify clusters based on NK cell surface markers from a combined dataset of healthy controls and Birdshot patients. Cluster 0 (CD56dim CD16+ CD8+ and CD244bright) is one out of 12 NK clusters that was elevated in Birdshot. Phenotypes of all 12 NK clusters are color coded and described. Healthy n = 11, Birdshot n = 18. C. Distribution of CD8a and D. CD244 surface protein expression is indicated in t-SNE plots of NK cells in five healthy controls (HC) and five birdshot uveitis (BCR-UV). Red dotted line captures the region where NK cells are present in BCR-UV but absent from HC. E. Histograms showing expression of CD314 (NKG2D) and CD344 (NKp44) in 10 healthy controls (blue) and 20 birdshot uveitis (red). All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.  All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

Figure S6
A. CD8 expression profiles in CD56bright and CD56dimCD16+ subsets of NK cells. B. CD69 expression in CD56dim CD16+ NK cells of healthy vs BCR-UV patients.
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